The vast majority of business organizations now, regardless of their size, use computer-aided systems to run their business processes. An example of such a system is a customer ordering system, wherein a customer can place an order for a good or material, and the business owner will process that order and provide the goods to the customer. When using such an ordering system, the customer may want to know if the merchandise will be available on a certain date. The system may determine/confirm this by performing an availability check. Such systems which perform an availability check may check for the availability of a material on a certain date, or whether the shipping essentials such as trucks will be available on a certain date. The point in time when the availability check is triggered, and/or the dates that are used for the availability check, are normally hard-coded into the business's ordering system. However, this causes problems because different business organizations and/or processes perform the availability checks at different points in the process and may use different dates. For example, a business process may need a particular material five days before a delivery date can be promised, whereas another business process may require the material 10 days prior to delivery. Similarly, one business process may need to check the availability date of the material within an internal plant, whereas a second business process may require checking the delivery date with regard to a specific customer or sales region quotation. Also, the critical link for one business process may be early on in the supply chain, while for another business process it may be later on in the supply chain. This causes problems for a large organization that may have multiple processes within the organization, and hence multiple order applications, or a software vendor who has to service many different clients with many different business processes. The art is therefore in need of a different process that can more flexibly handle such business processes.